Development of a Testbed and Quantitative Evaluation Framework for Characterization of Robot Actuator Dynamics
Deokgyu Kim, Samuel Kangwagye, Young Jin Heo, Sehoon Oh, Chan Lee
AI summary
Problem
Current actuator evaluation relies on static manufacturer specifications that fail to capture dynamic behaviors critical for physical interaction, leaving selection empirical and limiting real-world performance prediction.
Approach
The authors developed HYPERDYNE, a reconfigurable dynamometer-based testbed paired with a four-stage evaluation protocol to systematically extract dynamic parameters and compute quantitative performance metrics across position, velocity, and force control domains.
Key results
- A reconfigurable testbed supporting no-load, fixed-load, and interaction configurations without hardware disassembly
- A four-stage protocol extracting intrinsic mechanical parameters and control performance indices
- Quantitative benchmarking of a QDD actuator revealing 18 arcmin backlash and precise friction coefficients
- Objective metrics for tracking accuracy, load robustness, and disturbance rejection sensitivity
Why it matters
Provides robot developers and researchers with an objective framework to compare actuators and predict physical interaction performance, replacing empirical selection with data-driven benchmarking.
Abstract
The performance of robot actuators is still primar- ily evaluated using manufacturer-provided static specifications such as maximum torque and rated speed. However, these metrics are insufficient for assessing dynamic behaviors that are essential for physical interaction, including backdrivability, transparency, and disturbance response. This paper presents HYPERDYNE, a novel proof of concept test platform and evalu- ation framework for dynamic characterization and quantitative benchmarking of robot actuators. The reconfigurable testbed is developed, enabling three test configurations of no-load, fixed- load, and interaction scenarios within a single hardware setup. In addition, an evaluation protocol is proposed that includes system identification, control performance, load robustness, and disturbance rejection. Experimental validation on a QDD actuator demonstrates that the proposed framework enables the extraction of key dynamic parameters such as backlash, fric- tion, inertia, and frequency response characteristics, while also providing performance indices for objective comparison. The results show that actuator performance can be quantitatively assessed beyond conventional static specifications, supporting the development of robots with improved physical interaction capabilities.